package com.hmdp.service.impl;

import cn.hutool.core.util.BooleanUtil;
import cn.hutool.core.util.StrUtil;
import cn.hutool.json.JSONObject;
import cn.hutool.json.JSONUtil;
import com.baomidou.mybatisplus.extension.plugins.pagination.Page;
import com.hmdp.dto.Result;
import com.hmdp.entity.Shop;
import com.hmdp.mapper.ShopMapper;
import com.hmdp.service.IShopService;
import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
import com.hmdp.utils.CacheClient;
import com.hmdp.utils.RedisData;
import com.hmdp.utils.SystemConstants;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.geo.Distance;
import org.springframework.data.geo.GeoResult;
import org.springframework.data.geo.GeoResults;
import org.springframework.data.redis.connection.RedisGeoCommands;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.data.redis.domain.geo.GeoReference;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;

import java.time.LocalDateTime;
import java.util.*;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.TimeUnit;
import static com.hmdp.utils.RedisConstants.*;

/**
 * <p>
 *  服务实现类
 * </p>
 *
 * @author 虎哥
 * @since 2021-12-22
 */
@Service
public class ShopServiceImpl extends ServiceImpl<ShopMapper, Shop> implements IShopService {
    @Autowired
    private StringRedisTemplate stringRedisTemplate;

    @Autowired
    private CacheClient acheClient;
    @Override
    public Result queryById(Long id) {
        /** 用工具类解决缓存穿透问题 **/
        /* Shop shop  = acheClient
                .queryWithLogicalExpire(CACHE_SHOP_KEY, id, Shop.class, this::getById, CACHE_SHOP_TTL, TimeUnit.MINUTES);*/
        /** 用工具类里的互斥锁解决缓存击穿 **/
        Shop shop = acheClient
                .queryWithMutex(CACHE_SHOP_KEY, id, Shop.class, this::getById, 20L, TimeUnit.SECONDS);
        /** 缓存穿透**/
        // Shop shop = queryWithPassThrough(id);
        /** 互斥锁解决缓存击穿 **/
        // Shop shop = queryWithMutex(id);
        /** 逻辑过期解决缓存击穿 **/
       // Shop shop = queryWithLogical(id);
        if (shop == null){
            return Result.fail("商铺不存在");
        }
        return Result.ok(shop);
    }
    //尝试获取锁
    private boolean tryLock(String key) {
        Boolean flag = stringRedisTemplate.opsForValue().setIfAbsent(key, "1", 10, TimeUnit.SECONDS);
        return BooleanUtil.isTrue(flag);
    }
    //释放锁
    private void unLock(String key) {
        stringRedisTemplate.delete(key);
    }
    @Override
    @Transactional
    public Result update(Shop shop) {
        Long id = shop.getId();
        if (id == null) {
            return Result.fail("店铺id不能为空");
        }
        //1、更新数据库
        updateById(shop);
        //2、删除缓存
        String key = CACHE_SHOP_KEY + shop.getId();
        stringRedisTemplate.delete(key);
        log.debug("更新shop成功");
        return Result.ok();
    }

    @Override
    public Result queryShopByType(Integer typeId, Integer current, Double x, Double y) {
        // 1.判断是否需要根据坐标查询
        if (x == null || y == null) {
            // 不需要坐标查询，按数据库查询
            Page<Shop> page = query()
                    .eq("type_id", typeId)
                    .page(new Page<>(current, SystemConstants.DEFAULT_PAGE_SIZE));
            // 返回数据
            return Result.ok(page.getRecords());
        }

        // 2.计算分页参数
        int from = (current - 1) * SystemConstants.DEFAULT_PAGE_SIZE;
        int end = current * SystemConstants.DEFAULT_PAGE_SIZE;

        // 3.查询redis、按照距离排序、分页。结果：shopId、distance
        String key = SHOP_GEO_KEY + typeId;
        GeoResults<RedisGeoCommands.GeoLocation<String>> results = stringRedisTemplate.opsForGeo() // GEOSEARCH key BYLONLAT x y BYRADIUS 10 WITHDISTANCE
                .search(
                        key,
                        GeoReference.fromCoordinate(x, y),
                        new Distance(5000),
                        RedisGeoCommands.GeoSearchCommandArgs.newGeoSearchArgs().includeDistance().limit(end)
                );
        // 4.解析出id
        if (results == null) {
            return Result.ok(Collections.emptyList());
        }
        List<GeoResult<RedisGeoCommands.GeoLocation<String>>> list = results.getContent();
        if (list.size() <= from) {
            // 没有下一页了，结束
            return Result.ok(Collections.emptyList());
        }
        // 4.1.截取 from ~ end的部分
        List<Long> ids = new ArrayList<>(list.size());
        Map<String, Distance> distanceMap = new HashMap<>(list.size());
        list.stream().skip(from).forEach(result -> {
            // 4.2.获取店铺id
            String shopIdStr = result.getContent().getName();
            ids.add(Long.valueOf(shopIdStr));
            // 4.3.获取距离
            Distance distance = result.getDistance();
            distanceMap.put(shopIdStr, distance);
        });
        // 5.根据id查询Shop
        String idStr = StrUtil.join(",", ids);
        List<Shop> shops = query().in("id", ids).last("ORDER BY FIELD(id," + idStr + ")").list();
        for (Shop shop : shops) {
            shop.setDistance(distanceMap.get(shop.getId().toString()).getValue());
        }
        // 6.返回
        return Result.ok(shops);
    }


    /** 缓存穿透 **/
    public Shop queryWithPassThrough(Long id) {
        //解决缓存击穿
        //1、从redis中查询商铺缓存
        String key = CACHE_SHOP_KEY + id;
        String shopJson = stringRedisTemplate.opsForValue().get(key);

        //2、判断是否存在
        if (StrUtil.isNotBlank(shopJson)) {
            //3、存在，直接返回
            Shop shop = JSONUtil.toBean(shopJson, Shop.class);
            return shop;
        }
        //判断命中的是否是空值
        if (shopJson != null) {
            return null;
        }

        //4、不存在，去数据库中查询id
        Shop shop = getById(id);

        //5、不存在，返回错误
        if (shop == null) {
            //将空值写入redis，避免缓存穿透
            stringRedisTemplate.opsForValue().set(key, "", CACHE_NULL_TTL, TimeUnit.MINUTES);
            //返回错误信息
            return null;
        }

        //6、存在，写入redis
        stringRedisTemplate.opsForValue().set(key, JSONUtil.toJsonStr(shop), CACHE_SHOP_TTL, TimeUnit.MINUTES);

        //7、返回
        return shop;
    }
    /**互斥锁实现解决缓存击穿**/
    public Shop queryWithMutex(Long id){
        //1.从Redis内查询商品缓存
        String shopJson = stringRedisTemplate.opsForValue().get(CACHE_SHOP_KEY + id);
        if(StrUtil.isNotBlank(shopJson)){
            //手动反序列化
            return JSONUtil.toBean(shopJson, Shop.class);
        }
        //如果上面的判断不对，那么就是我们设置的""(有缓存"",证明数据库内肯定是没有的)或者null(没有缓存)
        //判断命中的是否时空值
        if(shopJson!=null){//
            return null;
        }

        //a.实现缓存重建
        //a.1 获取互斥锁
        String lockKey = LOCK_SHOP_KEY + id;
        Shop shop = null;
        try {
            boolean hasLock = tryLock(lockKey);
            //a.2 判断是否获取到，获取到:根据id查数据库 获取不到:休眠
            if(!hasLock){
                Thread.sleep(50);
                return queryWithMutex(id);
            }

            //2.不存在就根据id查询数据库
            shop = getById(id);
            //模拟重建的延时
            Thread.sleep(200);
            if(shop==null){
                stringRedisTemplate.opsForValue().set(CACHE_SHOP_KEY + id,"",CACHE_NULL_TTL,TimeUnit.MINUTES);
                return null;
            }
            //3.数据库数据写入Redis
            //手动序列化
            String shopStr = JSONUtil.toJsonStr(shop);
            stringRedisTemplate.opsForValue().set(CACHE_SHOP_KEY + id,shopStr,CACHE_SHOP_TTL, TimeUnit.MINUTES);
        } catch (InterruptedException e) {
            throw new RuntimeException(e);
        } finally {
            //释放互斥锁
            unLock(lockKey);
        }

        return shop;
    }

    /**缓存重建方法**/
    public void saveShop2Redis(Long id, Long expireSeconds) throws InterruptedException {
        //1.查询店铺信息
        Shop shop = getById(id);
        Thread.sleep(200);
        //2.封装逻辑过期时间
        RedisData redisData = new RedisData();
        redisData.setData(shop);
        redisData.setExpireTime(LocalDateTime.now().plusSeconds(expireSeconds));
        //3.写入Redis
        stringRedisTemplate.opsForValue().set(CACHE_SHOP_KEY+id,JSONUtil.toJsonStr(redisData));
    }

    private static final ExecutorService CACHE_REBUILD_EXECUTOR = Executors.newFixedThreadPool(10);//开启10个线程

    /**逻辑过期实现解决缓存击穿**/
    public Shop queryWithLogical(Long id){
        //1.从Redis内查询商品缓存
        String shopJson = stringRedisTemplate.opsForValue().get(CACHE_SHOP_KEY + id);
        //2.判断是否存在
        if(StrUtil.isBlank(shopJson)){
            return null;
        }
        //3.命中，需要先把json反序列化为对象
        RedisData redisData = JSONUtil.toBean(shopJson, RedisData.class);
        JSONObject data = (JSONObject) redisData.getData();
        Shop shop = JSONUtil.toBean(data, Shop.class);
        //4.判断是否过期
        LocalDateTime expireTime = redisData.getExpireTime();
        if(expireTime.isAfter(LocalDateTime.now())){
            //未过期直接返回
            return shop;
        }
        //5.过期的话需要缓存重建
        //5.1 获取互斥锁
        String lockKey = LOCK_SHOP_KEY + id;
        boolean hasLock = tryLock(lockKey);
        //5.2判断是否获取到，获取到:根据id查数据库 获取不到:休眠
        if(hasLock){
            //获取锁成功之后，还要再次检查数据是否过期，如果仍然过期，再开启线程
            //成功就开启独立线程，实现缓存重建, 这里的话用线程池
            CACHE_REBUILD_EXECUTOR.submit(()->{
                try {
                    //重建缓存
                    this.saveShop2Redis(id,20L);
                } catch (Exception e) {
                    throw new RuntimeException(e);
                }finally {
                    //释放锁
                    unLock(lockKey);
                }
            });
        }
        return shop;
    }
}

